By name: question-refiner description: Transform raw research questions into structured, validated research prompts with automatic research type detection and output format validation. Ensures prompts are ready for research-executor with comprehensive quality checks.
Question Refiner
Overview
Transform vague research questions into structured, actionable research prompts through strategic clarifying questions with automatic research type detection and quality validation.
When to Use
- User provides a raw, unstructured research question
- Research scope is unclear or too broad
- Need validated structured prompt for research-executor
- Want to ensure prompt meets quality standards (≥8.0)
Core Approach
Progressive Questioning (2 rounds max):
- Round 1 (3 questions): Topic focus, output format, audience
- Round 2 (conditional): Scope, sources, special requirements
- Auto-detect research type → Select template → Generate & validate
Research Type Detection
| Type | Indicators | Example |
|---|---|---|
| Exploratory | "what is", "overview", "landscape" | "What is the AI market like?" |
| Comparative | "vs", "compare", "difference" | "Compare GPT-4 vs Claude" |
| Problem-Solving | "how to", "solve", "fix" | "How to improve API performance" |
| Forecasting | "future", "trend", "prediction" | "Future of quantum computing" |
| Deep Dive | "technical", "architecture" | "How does BERT work internally" |
| Market Analysis | "market", "industry", "competition" | "AI chip market analysis" |
Output Structure
### RESEARCH TYPE
[auto-detected type]
### TASK
[Clear, specific research objective]
### CONTEXT/BACKGROUND
[Why this matters, who will use it]
### SPECIFIC QUESTIONS
1-7 concrete sub-questions
### KEYWORDS
[Search terms ≥5]
### CONSTRAINTS
- Timeframe: [e.g., 2020-present]
- Geography: [e.g., global]
- Source types: [academic, industry, news]
### OUTPUT FORMAT
- Type: [comprehensive_report|executive_summary|comparison_table]
- Citation style: [inline-with-url|footnotes]
### QUALITY SCORE
[0-10, must be ≥8.0]
Quality Validation
| Component | Weight | Criteria |
|---|---|---|
| Completeness | 30% | All required fields present |
| Specificity | 30% | Questions are specific, not vague |
| Keyword Richness | 20% | ≥5 search terms with synonyms |
| Constraint Clarity | 20% | Clear, realistic constraints |
Process: Generate → Validate → If score < 8.0: Refine (max 2 attempts)
Token Optimization
📋 Reference:
.claude/shared/constants/token_optimization.md
Context Budget: 10k tokens max
Error Handling
📋 Reference:
.claude/shared/constants/error_codes.md
- E001: Insufficient context → Ask clarifying questions
- E003: Validation failed → Refine and retry
- E004: Quality < 8.0 after retries → Request manual review
See also: Skill Base Template
Examples
See examples.md for detailed interaction patterns.
Detailed Instructions
See instructions.md for complete questioning strategy.